Manufacturing Engineer, Edge Supply Chain Manufacturing Engineering
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Minimum qualifications:
- Bachelor's degree or equivalent practical experience.
- Experience in manufacturing.
Preferred qualifications:
- Experience with supplier technical evaluations, qualifications, and managing supplier relationships.
- Experience with industry standards, including design guidelines and best practices for data center infrastructure.
- Proficiency with engineering and design software for modeling, analysis, and documentation.
- Knowledge of electromechanical, networking, and mechanical assembly processes, as well as tooling and equipment.
- Ability to conduct data analysis to identify trends, root causes of defects, and measure manufacturing performance.
- Ability to identify and resolve manufacturing and quality issues.
About the job
As a Data Center Manufacturing Engineer, you will act as the technical bridge between design innovation and operational reality, driving the product life-cycle from initial planning to mass production. You will be responsible for ensuring product manufacturability through early
design for excellence engagement and feasibility analysis, proactively identifying design risks before they impact the factory floor.
US: $99000 - $141000 (USD) + 15% bonus target + bonus + equity + benefits
Learn more about benefits at Google.
Responsibilities
- Lead design for excellence feasibility reviews and generate design for manufacturing (DFM) feasibility reports during concept readiness phase to resolve "red flag" features before design freeze.
- Validate mass production readiness through run-at-rate validation reports and line balancing charts to align takt time with cycle time.
- Execute vendor capability assessments and factory readiness gap analyses to ensure supply chain maturity. Enforce quality by reviewing process capability reports (Cpk > 1.33), control plans, and gage repeatability and reproducibility reports during the pilot phase.
- Advocate risk management by leading process failure mode and effects analysis (with risk priority number (RPN) reduction goals) and conducting pareto analysis and root cause analysis (8D) for any manufacturing issues.
- Optimize factory logistics by developing process flow diagrams and material presentation plans to audit and streamline how parts reach the production line.
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